The Chéliff watershed has one of the most spatially diverse pluviometric regimes in northwestern Algeria. Understanding these regimes is essential for managing water resources and identifying the most vulnerable regions to climate change. Mean annual rainfall data (1972–2012) for 58 meteorological stations and their corresponding elevation were used. Maps were produced using three geostatistical interpolation algorithms: ordinary kriging (OK), regression-kriging (RK), and kriging with external drift (KED); the first algorithm uses only rainfall while the other two use also elevation. Interpolation methods were compared using statistical indicators of cross-validation. Results indicate that KED is the least biased interpolator with limited number of strong underestimates or overestimates and limited relative importance of this strong underestimation or overestimation, followed by RK and finally OK. The best match between measured and predicted values was for KED (correlation coefficient of 0.82), followed by RK (0.79), while OK is far from them (0.70). KED can be considered the best model because it gives the lowest values of mean error, mean absolute error, and root mean square error (− 1.9, 35.4, and 49.5 mm, respectively) and the highest values of Willmott agreement index, Lin concordance coefficient, and Nash–Sutcliffe efficiency coefficient (0.89, 0.80, and 0.67, respectively), results of RK are intermediate, while those of OK are the worst. There is clearly significant improvement in the prediction performance taking into account the elevation, in particular by KED. Results show that KED is the most appropriate to produce map of mean annual rainfall in the Chéliff watershed, Algeria.

切利夫（Chéliff）分水岭是阿尔及利亚西北部空间上最多样化的测雨方式之一。了解这些制度对于管理水资源和确定最易受气候变化影响的地区至关重要。使用了58个气象站的平均年降水量数据（1972-2012年）及其相应的海拔。使用三种地统计插值算法生成地图：普通克里金法（OK），回归克里金法（RK）和带外部漂移的克里金法（KED）；第一种算法仅使用降雨，而其他两种算法也使用海拔。使用交叉验证的统计指标比较插值方法。结果表明，KED是偏差最小的插值器，其强低估或高估的数量有限，而这种强低估或高估的相对重要性有限，其次是RK，最后是OK。测量值和预测值之间的最佳匹配是KED（相关系数为0.82），其次是RK（0.79），而OK值离它们很远（0.70）。KED可以被认为是最佳模型，因为它给出了均值误差，均值绝对误差和均方根误差的最小值（分别为1.9、35.4和49.5 mm）以及Willmott一致性指数，Lin一致性系数的最大值，以及Nash-Sutcliffe效率系数（分别为0.89、0.80和0.67），RK的结果处于中间，而OK的结果最差。考虑到海拔高度，尤其是借助KED，预测性能显然有了显着提高。结果表明，KED最适合生成阿尔及利亚Chéliff流域的年平均降雨量图。